Journal of Work and Organizational Psychology 31 (2015) 187–200
Journal of Work and Organizational Psychology
www.elsevier.es/rpto
Original
The Work Design Questionnaire: Spanish version and validation
Jaime Andrés Bayona a , Amparo Caballer b , José-María Peiró b,c,∗
a
Pontificia Universidad Javeriana, Bogotá, Colombia
IDOCAL Research Institute, Universitat de Valencia, Valencia, Spain
c
Valencian Economic Research Institute (IVIE), Valencia, Spain
b
a r t i c l e
i n f o
Article history:
Received 3 September 2014
Accepted 1 June 2015
Available online 26 September 2015
Keywords:
Work design
Job characteristics
Test validation
Colombia
a b s t r a c t
The purpose of this study is to validate the Spanish version of the Work Design Questionnaire (WDQ;
Morgeson & Humphrey, 2006). Employees from three Colombian samples completed the questionnaire
(N = 831). Confirmatory factor analyses revealed a 21-factor structure (␹2 /df ratio = 2.40, SRMR = .06,
RMSEA = .04, CFI = .90) with adequate levels of convergent and discriminant validity. Additional support
for construct validity was found from significant differences among different occupational groups (professional and nonprofessional, health-focused, commercial, and manufacturing workers). Furthermore,
knowledge, social, and work context characteristics showed incremental validity over task characteristics
on job satisfaction and perceived performance. Possible interpretations of these relationships are offered.
It is concluded that the study provides evidence for the validity of a Spanish version of the scale, and
presents further support for the generalization of the 21-factor structure of work design characteristics
in different cultural settings.
© 2015 Colegio Oficial de Psicólogos de Madrid. Published by Elsevier España, S.L.U. This is an open
access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Validación española del Work Design Questionnaire
r e s u m e n
Palabras clave:
Diseño de trabajo
Características del trabajo
Validación de escalas
Colombia
El propósito de este estudio es validar la versión española del Work Design Questionnaire (WDQ; Morgeson y Humphrey, 2006). Tres muestras de empleados colombianos completaron el cuestionario (N = 831).
El análisis factorial confirmatorio reveló una estructura de 21 factores (razón ␹2 /gl = 2.40, SRMR = .06,
RMSEA = .04, CFI = .90) con adecuados niveles de validez convergente y discriminante. Se encontraron
diferencias significativas entre diferentes grupos ocupacionales (profesionales, no profesionales, trabajadores de la salud, comerciales y de producción). También se encontró que las características del
conocimiento, sociales y contextuales aportaron validez incremental sobre la satisfacción laboral y el
desempeño percibido. Se ofrecen posibles interpretaciones de estas relaciones. Se concluye que el estudio proporciona evidencia suficiente sobre la validez de la versión española de la escala, lo que presenta
más apoyo para la generalización de la estructura del modelo de características del trabajo de 21 factores
en diferentes contextos culturales.
© 2015 Colegio Oficial de Psicólogos de Madrid. Publicado por Elsevier España, S.L.U. Este es un
artículo Open Access bajo la licencia CC BY-NC-ND
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Work Design “describes how jobs, tasks, and roles are structured, enacted, and modified, as well as the impact of these
structures, enactments, and modifications on individual, group, and
organizational outcomes” (Grant & Parker, 2009, p. 319). From the
∗ Corresponding author: IDOCAL University of Valencia. Avda. Blasco Ibáñez, 21
46010 Valencia. Spain.
E-mail address: [email protected] (J.-M. Peiró).
early studies on task attributes (Turner & Lawrence, 1965) to the
interdisciplinary approach to work design (Campion, 1988), it has
been a demand, from both scientists and practitioners, to have
a valid and reliable instrument assessing work characteristics in
organizational settings. During the last 30 years questionnaires
such as the Job Diagnostic Survey (JDS; Hackman & Oldham, 1975)
and the Multimethod Job Design Questionnaire (MJDQ; Campion,
1985) have been developed to assess work design characteristics; however, these instruments generally have suffered from two
http://dx.doi.org/10.1016/j.rpto.2015.06.001
1576-5962/© 2015 Colegio Oficial de Psicólogos de Madrid. Published by Elsevier España, S.L.U. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
188
J.A. Bayona et al. / Journal of Work and Organizational Psychology 31 (2015) 187–200
drawbacks: (a) questionable psychometric properties related with
the low internal consistency of the JDS (Kulik, Oldham, & Langner,
1988; Taber & Taylor, 1990) and problems with the factor structure of the MJDQ (Edwards, Scully, & Brtek, 1999, 2000); and
(b) a mismatch between the work characteristics assessed by the
instruments and the real characteristics presented in nowadays
organizational settings, that is represented in a shift from manufacturing economies to service and knowledge economies that had
altered the nature of work in organizations (Grant & Parker, 2009).
Due to these limitations, Morgeson and Humphrey (2006) developed the Work Design Questionnaire (WDQ), that presents both high
reliable psychometrics and takes into account current models of
work design (Grant, Fried, & Juillerat, 2010; Humphrey, Nahrgang,
& Morgeson, 2007).
This need for a valid and reliable instrument is especially relevant in non-English speaking countries, where work dynamics have
changed during the last 20 years and old work design instruments
are no longer appropriate for these new organizational settings.
Thus, the purpose of the present study is to validate a Spanish
version of the WDQ with a sample of Colombian workers.
Work Characteristics Assessment
From the early work of Turner and Lawrence (1965), work
characteristics have been assessed mainly through self-report
questionnaires that ask workers to rate their personal evaluation of
the presence of certain work attributes. Using this approach, two
major work design questionnaires have been developed: the Job
Design Survey (JDS) and the Multimethod Job Design Questionnaire
(MJDQ).
Richard Hackman and his colleagues developed the JDS as an
instrument to assess the job characteristics model (JCM) (Hackman &
Lawler, 1971; Hackman & Oldham, 1975, 1976), which has been the
standard model in work design for both academics and practitioners during the last 40 years. The JDS is a self-reporting instrument
meant to diagnose the motivational properties of a job prior to a
redesign procedure. The major contribution of the JCM and JDS was
that it established that core job characteristics are associated with
favorable attitudinal and behavioral reactions (Grant et al., 2010).
However, the main criticisms to JCM were: (a) the treatment of
within-person relations as person-situation relations, (b) the model
structure, due to some inconsistences in the role of the moderator
and mediators, (c) the small subset of characteristics included in the
model, (d) concerns about the convergent and divergent validity of
the JDS, and (e) the theoretical and mathematical justification of the
composite job characteristics index (Fried & Ferris, 1987; Johns, Xie,
& Fang, 1992; Roberts & Glick, 1981).
Taking into account some of these criticisms, a new model
of work design emerged: the interdisciplinary model of job design
(Campion, 1988; Campion & Thayer, 1985) which aimed to develop
a new taxonomy of work design that included 48 different job characteristics with a 48-item questionnaire. The major strengths of this
approach were: (a) the inclusion of new work characteristics that
were relevant to the work context and (b) the discovery that different job design approaches influence different outcomes. On the
other side, the major weakness of the interdisciplinary model lay
in the psychometric proprieties of the MJDQ, especially the construct validity, since every dimension was assessed by only one
item (Edwards et al., 1999).
From these previous models, Frederick Morgeson and Stephen
Humphrey developed an inductively generated collection of work
design characteristics that integrated the work design literature
into four major work characteristics: (a) Task Characteristics,
which include work scheduling autonomy, decision-making autonomy, work methods autonomy, task variety, task significance, task
identity, and feedback from job; (b) Knowledge Characteristics,
which include job complexity, information processing, problem
solving, skill variety, and specialization; (c) Social Characteristics, which include social support, initiated interdependence,
received interdependence, interaction outside the organization
and feedback from others; and (d) Work Context Characteristics,
which include ergonomics, physical demands, work conditions,
and equipment use (Morgeson & Humphrey, 2006). This taxonomy integrated some elements of previous models but included
new characteristics that are present in today’s organizations (i.e.,
knowledge characteristics that reflect the current knowledge work
and social characteristics that reflect the emphasis on service organizations that rely more deeply on social interactions).
The construction of the WDQ was developed through five stages:
(a) review of job characteristics in the literature and grouping of the
resulting characteristics into a 21 characteristics proposal, (b) literature review to search items that evaluate each job characteristic,
(c) adapting items and creating new items for the 21 characteristics
proposal, (d) statistical analyses of the 21 job characteristics proposal using confirmatory factor analysis (CFA), and (e) construct
validity analyses using O*NET database and checking relationship
between occupations and various outcome measures (Morgeson &
Humphrey, 2006). The results of this procedure gave support to
a 21-factor structure with a high reliability and convergent and
discriminant validity, which in turn resolved two of the major criticisms of previous work design instruments: the limited number
of job characteristics considered (JDS) and the weak psychometrics
(MJDQ).
Work Design in Spanish Speaking Countries
All preceding models were developed within the North American context, with research on work design in Spanish speaking
countries dealing mainly with: (a) the validation of work design
instruments in their cultural settings or (b) the use of a work design
instrument as a measure within a broader research.
The research on work design in Spanish speaking countries
from a validation perspective includes a couple of JDS validations (Dávila & Chacón, 2003; Fuertes, Munduate, & Fortea, 1996;
Martínez-Gómez & Marín-García, 2009) which confirmed the 5factor dimension structure but with some reliability problems,
especially in the skill variety, autonomy, and identity dimensions. From the second perspective, the work design research on
those countries was particularly associated with the use of JCM.
In Spain there had been a number of studies using the JDS, as
in a study of burnout, organizational climate, and work motivation (Boada, Vallejo, & Agulló, 2004), in which three out of five
JCM dimensions were associated with different burnout outcomes
(autonomy, skill variety, task significance). Other research studied
the influence of communication skills on work teams management (Ramis, Manassero, Ferrer, & García-Buades, 2007), in which
no direct effect of job characteristics was associated with leader
communication skills. Finally, a study on the redesign of tasks in
the Spanish automotive industry concluded that all JCM dimensions were related with attitudinal outcomes (especially autonomy
and feedback), but not with any performance outcomes (Osca
& Urien, 2001). In Latin America, research on work design was
more limited: two studies, including the JDS, were conducted in
Perú, one that sought to explore the utility of the socio-technical
systems theory in that country, which reported a significant influence of feedback on the degree of technology implementation
(Salas & Glickman, 1990); the other study, by Solf (2006), used
a section of JDS (employee growth need strength) to investigate
labor intrinsic motivation and personality in a sample of Peruvian
workers.
J.A. Bayona et al. / Journal of Work and Organizational Psychology 31 (2015) 187–200
These studies in Spanish speaking countries indicate that there
is an interest in the design area, even though the tools available
offered a limited range of job characteristics and the psychometric specifications were not the most appropriate nowadays. Taking
these problems into account, the purpose of the present research
is to bridge this gap by adapting the WDQ to the Spanish language,
which will offer researchers and practitioners a valid and reliable
instrument to work with Spanish-speaking workers in the area of
work design.
Hypotheses Development
In this paper we describe the adaptation process of the WDQ
into Spanish. We tested the psychometric properties of the adapted
version through a variety of means. First, we conducted a series of
CFAs to confirm the factor structure of the Spanish adaptation; second, we further examined the psychometric properties of the scale
by testing its capacity to differentiate across occupations; third,
we explored the relations of major work characteristics with job
satisfaction and perceived performance; finally, we examined the
incremental validity of work characteristics for job satisfaction and
perceived performance.
In the original article about WDQ, five different factor structure models were tested: (a) a 4-factor model examines the four
broad categories of work characteristics (task, knowledge, social,
and context); (b) an 18-factor model examines each work characteristic; (c) a 19-factor model separates interdependence into its
received and initiated components; (d) a 20-factor model separates
autonomy into its three components, which includes autonomy in
work scheduling, decision making, and work methods; (e) finally,
a 21-factor model separates both interdependence and autonomy
into the identified components. Following the results from the original English version (Morgeson & Humphrey, 2006) and the German
(Stegmann et al., 2010) and Italian (Zaniboni, Truxillo, & Fraccarolli,
2013) validations of the WDQ, it is expected that the Spanish version of the WDQ will fit into a 21-factor model.
Hypothesis 1.
structure.
The Spanish WDQ version represents a 21-factor
In order to validate the WDQ, it is important that the Spanish
version could detect differences across occupations according to
their job and role contents, because the original WDQ is aimed at
differentiating between jobs, and thus, the Spanish version should
be able to differentiate between different classes of jobs. In the
original WDQ validation article, four different occupational groups
were compared in different work characteristics (professional, nonprofessionals, human-life occupations, and sales occupations). In
line with this procedure, we examined the differences in work
characteristics in four groups. First, we expected that “jobs in professional occupations would be higher on both the broad set of
knowledge characteristics and the three components of autonomy
than jobs in nonprofessional occupations, because professional
occupations generally involve complex, non-routine work that
requires flexible and adaptive behavior where higher levels of
autonomy are present” (Morgeson & Humphrey, 2006, p. 1328).
Second, we expected “jobs in nonprofessional occupations, compared with those in professional occupations, to be higher on
physical demands and lower in the quality of work conditions
because these jobs generally involve more physical exertion in less
than optimal work environments” (Morgeson & Humphrey, 2006,
p. 1328). Third, we expected jobs in health related occupations to
be higher on task significance because behavior in these occupations directly affect human lives (Morgeson & Humphrey, 2006).
Finally, we expected jobs in commercial occupations to be higher
on interaction outside the organization because sales occupations
are specifically focused on providing products and services to
189
others (Morgeson & Humphrey, 2006). According to this rationale
we formulate the following hypotheses.
Hypothesis 2a. Professional occupations will have higher levels
of knowledge and autonomy characteristics than nonprofessional
occupations.
Hypothesis 2b. Nonprofessional occupations will have higher levels of physical demands and less positive work conditions than jobs
in professional occupations.
Hypothesis 2c. Jobs in health occupations will have higher levels
of task significance than manufacturing occupations.
Hypothesis 2d. Jobs in commercial occupations will have higher
levels of interaction outside organization than manufacturing occupations.
Research on work design has found a positive relationship
between task characteristics and attitudinal (i.e., job satisfaction)
and behavioral (i.e., performance) outcomes (Fried & Ferris, 1987;
Hackman & Oldham, 1980). In the original WDQ validation article,
task and knowledge characteristics were compared to job satisfaction. In addition, some research has stated that the new work design
characteristics (e.g., knowledge and social ones) will show a similar
relation to job satisfaction and perceived performance (Grant et al.,
2010; Grant & Parker, 2009). Following this rationale we expected
that task, knowledge, and social characteristics would be related to
both job satisfaction and perceived performance.
Hypothesis 3. Task, knowledge and social characteristics will be
positively related to job satisfaction (Hypothesis 3a) and perceived
performance (Hypothesis 3b).
In the original WDQ validation article, social support was
expected to incrementally predict satisfaction beyond task characteristics; however, due to changes in the nature of work that
emphasizes more knowledge and service jobs than industrial ones
(Grant & Parker, 2009), and due to the characteristics of LatinAmerican countries in which social relations are highly valued
(Hofstede, 2001; House, Hanges, Javidan, Dorfman, & Gupta, 2004),
it is expected that both knowledge and social characteristics will
influence job satisfaction and perceived performance in an incremental rate. In addition, although some authors considered that
context characteristics explained little variance in job satisfaction
(Humphrey et al., 2007), others reported that work context characteristics had an important role in job satisfaction and different
indicators of performance (Conlon & Dyne, 2004). Following this
rationale we expected that social, knowledge, and work context
characteristics would explain an important amount of variance for
both job satisfaction and perceived performance.
Hypothesis 4. Knowledge, social and work context characteristics
will demonstrate incremental validity above the task characteristics for job satisfaction (Hypothesis 4a) and perceived performance
(Hypothesis 4b).
Method
Translation
The translation of the WDQ into Spanish was accomplished
through the translation/back-translation procedure recommended
by Brislin (1980). The researchers first translated the WDQ from
English to Spanish and then a bilingual professional translator with
experience in the Business Administration field back-translated
the Spanish version into English. Following the translation from
English to Spanish, we compared the original questionnaire to
the back-translated English version and differences were resolved
through discussion among authors; the professional translator was
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J.A. Bayona et al. / Journal of Work and Organizational Psychology 31 (2015) 187–200
not aware of the study purpose. The wording of items was aimed to
reflect general forms rather than specific idioms and expressions of
the Spanish language as it is spoken in different countries. An initial
version of the questionnaire was tested with a group of 18 workers from different occupational levels; once the questionnaire was
administered, an interview with these workers was conducted in
order to identify problems with the language expressions or wording. The resulting Spanish questionnaire used in the validation is
presented in the Appendix.
Participants and Procedure
The sample was collected in Colombia, a country classified as an
upper-middle-income economy with a GDP per capita (purchasing
power parity) of US$ 9,125 (USA, US$ 43,063), an average economic growth from 2007 to 2011 of 4.5%, an annual employment
growth of 3.5%, and 46.4% of its total work force being wage and
salaried workers (USA, 93.2%); 77.2% of these salaried workers are
distributed across four main economic sectors: wholesale and retail
service (26.4%), health and social work (19.9%), agriculture, forestry,
and fishing (17.5%), and manufacturing (13.4%); this same four economic sectors represent the 40.5% distribution of salaried workers
in the USA (International Labour Organization, 2013a, 2013b).
Eight hundred forty-one Colombian employees participated in
the study; however, 10 questionnaires were not usable due to
participants not responding the WDQ section, leaving 831 useful
questionnaires. The mean age for all participants was 34.9 years
(range: 18-70, SD = 11 years); the mean tenure for all participants
was 6.05 years (range: 1-51, SD = 7.48 years); 43% of workers were
females (98.5 valid percent), 7.7% of respondents had completed
education only at a high school/diploma level, 69.9% had completed
undergraduate level (university, technical, or technological education), and 16.2% had completed postgraduate level or higher (93.8
valid percent).
Data were collected from three different samples. Sample 1
consisted of 279 full-time employees working for an organization that manufactures pumps, compressors, and valves (83.5%
men; age: M = 31.2 years, SD = 8.2 years; education: M = 14.4 years,
SD = 3.5 years); this sample included both blue and white collar
workers. Sample 2 consisted of 89 full-time administrative employees working for a university (37% men; age: M = 39.3 years, SD = 8.8
years; education: M = 14.3 years, SD = 5.2 years). Sample 3 consisted
of 463 full-time employees working for different organizations
(44% men; age: M = 36.2 years, SD = 12.3 years; education: M = 16.2
years, SD = 4.1 years). Sample 3 was obtained in the context of an
organizational behavior course with junior-level business administration students. These students analyzed the work of a family
member or acquaintance (job incumbent) who has worked full
time for at least one year, and administrated the WDQ to the job
incumbent (the students received specific training on the application of the questionnaire from one of the authors). This particular
sampling strategy was employed so data could be collected on a
wide range of jobs following the strategy used in the original work
of Morgeson and Humphrey (2006) and is used when the goal is
to sample a wide range of different jobs (e.g., Raymark, Schmit, &
Guion, 1997). Workers in all samples filled a paper-and-pencil version of the WDQ and were informed about the confidential use of all
information provided. The procedures were approved by the ethics
review board of Pontificia Universidad Javeriana before the study
began.
The distribution of the whole sample, depending on the economic sector in which job incumbents work, can be seen in
Table 1. This distribution includes 17 out of 21 economic activities considered in the International Standard Industrial Classification
of All Economic Activities (ISIC) (United Nations, 2008). However,
it is important to note the under-representation of the agriculture, forestry and fishing sector, which has a very important
role in the Colombian economy. The explanation for this underrepresentativeness is because sample was collected in an urban
context and the access to these workers is difficult. Nevertheless,
apart from this sector, the sample reflects the general formal labor
market composition in Colombia.
Occupational classification. We created five broad occupational
categories (i.e., professional, non-professional, health, commercial, and manufacturing occupations) to test the occupational
focused hypothesis (H2a, H2b, H2c, H2d). For professional and nonprofessional classification, job incumbents self-reported if their
occupation was professional (their work activities require a university degree) or nonprofessional (their work activities do not require
a university degree). For the other categories (health, commercial, and manufacturing occupations), job incumbents self-reported
the economic sector in which their organization was located
using the ISIC classification (Table 1). For sample 1 (manufacture organization), all workers were classified in the manufacture
Table 1
Incumbent Population by ISICa
ISIC occupation category
Agriculture forestry and fishing
Mining and quarrying
Manufacturing
Construction
Wholesale and retail service
Transportation and storage
Accommodation and food service activities
Information and communication
Financial and insurance activities
Real estate activities
Professional, scientific and technical activities
Administrative and support service activities
Public administration and defense; compulsory social security
Education
Human health and social work activities
Arts, entertainment and recreation
Other services activities
No information
Total
n
4
14
327
42
25
5
9
22
37
5
29
9
33
128
33
2
5
102
831
Note. All samples included.
a
International Standard Industrial Classification of All Economic Activities.
Age (years)
Job tenure (years)
M
SD
M
SD
44.00
41.43
33.06
34.13
33.96
43.80
29.78
37.62
36.19
41.40
33.55
34.56
41.50
38.93
41.18
36.00
35.36
29.70
34.92
8.52
11.91
9.66
11.15
12.92
11.30
13.34
13.70
11.49
17.44
11.30
7.13
12.67
10.12
10.74
12.73
7.86
10.92
11.12
7.85
7.98
4.35
4.49
4.72
17.12
3.43
4.55
8.16
4.82
3.52
6.25
10.24
10.07
10.00
11.38
2.00
4.48
6.05
9.53
9.21
5.96
8.84
7.26
21.13
4.70
6.12
7.61
4.53
4.65
8.57
9.12
8.16
9.42
15.50
1.03
5.30
7.47
Sex
(% men)
50
50
78
60
48
80
22
50
49
60
24
67
24
33
33
100
20
47
56
J.A. Bayona et al. / Journal of Work and Organizational Psychology 31 (2015) 187–200
sector; for sample 2 (university), all workers were classified in
the education sector; for sample 3 (different organizations), business administration students helped the job incumbents to report
this information. The “health” category was composed of the jobs
within the “human health and social work activities” of the ISIC
classification, whereas the “non-health” category was composed of
the jobs in the remaining occupations. The “commercial” category
was composed of the jobs within the “wholesale and retail service”
of the ISIC classification. Finally, the “manufacturing” category was
composed of the jobs within the “manufacturing” group in the ISIC
classification.
A one-way ANOVA was conducted in order to verify any possible differences in demographic variables among the samples. For
age, tenure, and education, significant differences were detected:
age, F(2, 802) = 26.02, p ≤ .01 (sample 1, M = 31.2 years, sample 2,
M = 39.3 years, sample 3, M = 36.2 years); tenure, F(2, 811) = 42.88,
p ≤ .01 (sample 1, M = 3.1 years, sample 2, M = 10.3 years, sample 3,
M = 7 years); education, F(2, 778) = 19.21, p ≤ .01 (sample 1, M = 14.4
years, sample 2, M = 14.3 years, sample 3, M = 16.2 years). Because
of these results, analyses that use full-sample will be performed
using these three variables as controls on the regression model of
hypotheses 4a and 4b.
Measures
Work design. We used the WDQ developed by Morgeson and
Humphrey (2006) that is a self-reporting measure that includes 77
items using a 5-point Likert scale ranging from 1 (strongly disagree)
to 5 (strongly agree). Cronbach’s alpha of the original version of the
WDQ ranged from .64 (ergonomics) to .95 (task variety and physical
demands), with a mean alpha = .86.
Job satisfaction was measured using the 4-item job satisfaction
scale developed by De Witte (2000) in its Spanish version used by
Isaksson (2007). The scale uses a 5-point Likert scale ranging from 1
(nothing important) to 5 (extremely important). The Spanish version
Cronbach’s alpha = .81. An example item is: “La mayoría de los días
estoy entusiasmado/a con mi trabajo.”
Perceived performance was measured through the 6-item
perceived performance scale developed by Abramis (1994) in its
Spanish version used by Isaksson (2007). This scale asks respondents to think about their previous week at work and to rate how
well they performed on six tasks, namely decision-making, performing without making mistakes, goal attainment, effort, taking
initiatives, and taking responsibility. Five response categories were
used, ranging from 1 (very badly) to 5 (very well). The Spanish version Cronbach’s alpha = .79. An example item is: “¿En qué medida
ha realizado satisfactoriamente la siguiente tarea? - Trabajar sin
cometer errores.”
Analyses
To test hypothesis 1, we used confirmatory factor analysis (CFA)
conducted with AMOS 21 (Arbuckle, 2012). We applied a maximum
likelihood estimation method; in order to run this analysis, no missing data will be allowed; taking into account that the missing data
pattern was completely at random (Schafer & Graham, 2002) and
that the missing data percentage was less than 2% per variable, a
mean imputation was done using SPSS. Maximum skewness was
-1.74 and maximum kurtosis was 3.83, which is among the recommended bounds for skewness |2.0| and kurtosis |7.0| (Hancock &
Mueller, 2010).
Consistent with Morgeson and Humphrey (2006), we report various fit indices: ␹2 /df ratio, comparative fit index (CFI), standardized
root-mean-square residual (SRMR), and root-mean-square error
of approximation (RMSEA). For ␹2 /df ratio, a value of 2.0 indicates good fit. For CFI, values higher than .90 indicate good fit. For
191
SRMR, values lower than .08 indicate good fit. For RMSEA a value
of .05 indicate good fit. We used the chi-square difference (␹2 ) to
compare the models, and accepted the more parsimonious model
if it was not significantly different from a more complex model. We
tested five different models of work design using CFA techniques:
• 4-factor model examines the four broad categories of work
characteristics (i.e., task, knowledge, social, and work context
characteristics).
• 18-factor model examines the work characteristics without any
divisions (i.e., autonomy and interdependence as unique factors).
• 19-factor model separates interdependence into its received and
initiated components.
• 20-factor model separates autonomy into its three components,
which includes autonomy in work scheduling, decision making,
and work methods.
• 21-factor model separates both interdependence and autonomy
into the identified components.
To test hypotheses 2a, 2b, 2c and 2d we used t-tests to
compare means of two occupational segments: professional and
non-professional workers, health and manufacturing workers,
commercial and manufacturing workers. To test hypothesis 3a and
3b we performed bivariate Pearson correlations; finally, to test
hypothesis 4a and 4b, we used hierarchical regression analyses
aiming to compute incremental validity, which determined the
variance accounted for knowledge, social, and work context characteristics in job satisfaction and perceived performance beyond
the variance explained by task characteristics.
Results
Table 2 presents the descriptive statistics of WDQ Scales. The
first two columns present the means and standard deviations;
overall there is no evidence of floor or ceiling effects. The third
column presents Cronbach’s alpha (␣). In overall, the scales of
the Spanish version of the WDQ demonstrate very good internal
consistency reliability, and only in ergonomics the coefficients are
somewhat low in ␣ (bellow .6). The fourth, fifth, and sixth columns
present interrater reliability (intraclass correlation or ICC[2]; Bliese,
2000) and interrater agreement (rwg(j) ; James, Demaree, & Wolf,
1984). The ICC[2] assesses the extent to which incumbent judgments of their ISIC categories covary with each other relative to
incumbents in other ISIC categories. The rwg(j) reflects the absolute
level of agreement across raters and thus assesses the extent to
which raters make similar mean-level ratings across their ISIC categories (Morgeson & Humphrey, 2006). Generally, these statistics
suggest that the incumbents within an ISIC occupational category
agree on their work characteristics assessment. As in the original
WDQ, there were some exceptions: task variety, task significance,
job complexity, and problem solving. These variables demonstrate
essentially zero interrater reliability. As Morgeson and Humphrey
(2006) pointed, this could be due to a “lack of between-job variability in this sample or that perhaps these aspects of work are not
stable characteristics of a job and reflect idiosyncratic elements of
job holders” instead (Morgeson & Humphrey, 2006, p. 1326). Yet,
the high levels of interrater agreement (rwg(j) ) would suggest that
these are not idiosyncratic perceptions because multiple incumbents agreed in their perceptions. Because job incumbents among
an occupational category could hold different hierarchical levels,
additional ICC[2] analyses using hierarchical level as the grouping
variable were performed; results showed in Table 2 present ICC[2]
values ranging from .54 to .97, p ≤ .05, for 20 out of 21 work characteristics. Taken as a whole, these data suggest that it is appropriate
192
J.A. Bayona et al. / Journal of Work and Organizational Psychology 31 (2015) 187–200
Table 2
Means, Standard Deviations and Reliability.
Construct
Task characteristics
Work scheduling autonomy
Decision-making autonomy
Work methods autonomy
Task variety
Task Significance
Task identity
Feedback from job
Knowledge characteristics
Job complexity
Information processing
Problem solving
Skill variety
Specialization
Social characteristics
Social support
Initiated interdependence
Received interdependence
Interaction outside organization
Feedback from others
Work context characteristics
Ergonomics
Physical demands
Work conditions
Equipment use
M
SD
Internal
consistencya
ISIC Interrater
reliabilityb
Hierarchical level
Interrater
reliabilityb
Interrater
agreementc
Convergentdiscriminant
validity
AVE
MSV
3.87
3.59
3.72
4.05
4.20
3.90
4.00
0.88
0.87
0.82
0.84
0.65
0.72
0.75
.86
.84
.83
.91
.76
.82
.87
.64**
.50**
.61**
−.03
.18
.70**
.54**
.97**
.97**
.96**
.87**
.83**
.89**
.66*
.80
.77
.80
.82
.88
.88
.88
.68
.65
.61
.71
.49
.57
.70
.68
.70
.70
.11
.12
.30
.30
3.47
3.98
3.63
3.89
3.63
0.87
0.76
0.74
0.77
0.79
.80
.80
.67
.91
.85
−.49
.45*
.07
.54**
.58**
.93**
.97**
.92**
.95**
.95**
.74
.84
.75
.85
.80
.58
.51
.36
.73
.59
.13
.48
.48
.48
.36
4.00
3.56
3.49
3.27
3.23
0.65
0.89
0.89
1.14
0.93
.81
.75
.75
.92
.84
.69**
.68**
.41*
.85**
.73**
.54†
.56*
.77**
.94**
.96*
.92
.68
.67
.63
.74
.44
.53
.52
.75
.65
.17
.53
.53
.12
.17
3.54
2.31
3.43
2.85
0.82
1.10
0.88
0.96
.57
.95
.76
.75
.66**
.79**
.86**
.65**
.92**
.98**
.97**
.88**
.69
.73
.67
.50
.49
.86
.40
.50
.34
.21
.34
.21
Note. All samples included. ␣ = Cronbach’s alpha; AVE = average variance extracted; MSV = maximum shared squared variance.
a
Coefficient alpha.
b
ICC[2].
c
rwg(j)
†
p < .10, * p < .05, ** p < .01.
to aggregate to the occupational category (ISIC) and there are high
levels of agreement about a job’s category on work characteristics.
Confirmatory Factor Analysis
In order to test the first hypothesis, that the Spanish WDQ version will fit a 21-factor structure, we run a set of five different CFAs.
The results of our CFAs are presented in Table 3, broken down for
each sample. First, for the full sample, the 4-factor model showed
poor fit, as the fit indexes were all off the accepted levels. Second, the 18-, 19-, and 20-factor solutions showed adequate fit,
with the SRMR and RMSEA reaching adequate levels, whereas the
CFI was slightly low and the ␹2 /df was slightly high. Finally, we
tested the 21-factor solution; this model was the best fitted model
overall, with the lowest ␹2 /df ratio, SRMR, RMSEA and the highest
CFI. This model was significantly better than the 18-factor model
(␹2 change = 627, df change = 57, p < .001), the 19-factor model (␹2
change = 424, df change = 39, p < .001) and the 20-factor model (␹2
change = 204, df change = 20, p < .001). These same results patterns
are present in the separate analyses for each sample (Table 3); thus,
like the original WDQ, the 21-factor model, which separates interdependence in two factors and autonomy in three factors, fits our
data the best.
Additional evidence for a 21-factor structure is provided when
the structure of task and social characteristics are studied separately. For task characteristics, a comparison between 5- and
7-factor model was developed (separating or integrating the three
dimensions of autonomy). The 7-factor model performed better in
␹2 /df ratio in comparison to the 5-factor model (␹2 change = 372,
df change = 11, p < .001), SRMR = .08, RMSEA = .07, CFI = .93). For
social characteristics, a comparison between a 4- and a 5-factor
model was developed (separating or integrating the two dimensions of interdependence); the 5-factor model performed better in
␹2 /df ratio than the 4-factor model (␹2 change = 184, df change = 4,
p < .001), SRMR = .06, RMSEA = .07, CFI = .92). In sum, these data fully
support hypothesis 1.
Convergent/Discriminant Validity
Once we confirmed the 21-factor measurement model, it is
important to assess the extent to which the items of a specific factor
converge or share a high proportion of variance (convergent validity). In addition, it is also important to assess the extent to which a
factor is truly distinct from other factors both in terms of how much
it correlates with other factors and how distinctly items represent
only this single factor (discriminant validity).
To evaluate convergent validity, two methods were used: (a)
assessment of standardized factor loadings of observable variables
and (b) average variance extracted (AVE) for each factor. For the
first method, a comparison of factor loadings of each item was conducted, loadings estimates should be significant and with a factor
loading of .50 or higher for the associated item; for the AVE method,
“the average variance extracted is calculated as the mean variance
extracted for the item loading on a [factor] and is a summary indicator of convergence” (Hair, Black, Babin, & Anderson, 2010, p. 687)
and values greater than .50 are considered adequate.
On the other hand, to evaluate discriminant validity, a comparison between the AVE and the maximum shared squared variance
(MSV) of each factor was carried out; the MSV represents the maximum shared squared variance found when comparing for any two
factors (in this case, each factor was compared with all other 20
factors); with the square of the correlation estimate between these
J.A. Bayona et al. / Journal of Work and Organizational Psychology 31 (2015) 187–200
193
Table 3
Results of Confirmatory Factor Analysis.
Model
4-factor
Full sample
Sample 1
Sample 2
Sample 3
18-factor
Full sample
Sample 1
Sample 2
Sample 3
19-factor
Full sample
Sample 1
Sample 2
Sample 3
20-factor
Full sample
Sample 1
Sample 2
Sample 3
21-factor
Full sample
Sample 1
Sample 2
Sample 3
2
df
2 /df ratio
SRMR
RMSEA
CFI
21544
8888
7319
14562
2843
2843
2843
2843
7.58
3.13
2.57
5.12
.12
.12
.14
.13
.09
.08
.13
.09
.49
.44
.31
.47
6972
4659
5503
5613
2696
2696
2696
2696
2.59
1.73
2.04
2.08
.06
.07
.11
.06
.04
.05
.11
.05
.88
.82
.57
.87
6769
4606
5449
5468
2678
2678
2678
2678
2.53
1.72
2.04
2.04
.06
.07
.11
.06
.04
.05
.11
.05
.89
.82
.58
.87
6549
4523
5329
5342
2659
2659
2659
2659
2.46
1.70
2.00
2.01
.06
.07
.11
.06
.04
.05
.11
.05
.89
.83
.59
.88
6345
4470
5274
5197
2639
2639
2639
2639
2.40
1.69
2.00
2.00
.06
.07
.11
.06
.04
.05
.11
.05
.90
.83
.60
.89
Note. SRMR = standardized root-mean-square; RMSEA = root-mean-square error of approximation; CFI = comparative fit index.
two factors, the AVE estimates should be greater than the MSV; this
is because “a latent [factor] should explain more of the variance in
its item measures that it shares with another construct” (Hair et al.,
2010, p. 688); when the MSV values are lower than the AVE, the
measure has good discriminant validity.
The results for convergent validity indicate that the standardized factor loadings of the WDQ indicate average estimate of .74,
with just 4 out of 77 items below .50 (items 15, 18, 25, and 66).1
For the AVE method, as shown in Table 2, the values of 5 out of
21 factors were below .50: task significance .49, problem solving
.36, social support .44, ergonomics .49, and work conditions .40.
Taken together, the evidence supports the convergent validity of
the measurement model (with some limitations in the factors just
mentioned).
On the other side, for discriminant validity, some values of MSV
were below the AVE values, indicating some issues in the autonomy
factors (work scheduling, decision making, and work methods),
interdependence factors (initiated and received) and problem solving factor; however, the other 15 factors showed adequate levels
of divergent validity.
autonomy, t(789) = 10.96, r2 = .14, p < .001; decision-making autonomy, t(696) = 9.54, r2 = .11, p < .001; and work methods autonomy,
t(789) = 8.90, r2 = .09, p < .001. Thus hypothesis 2a was fully supported.
Second, hypothesis 2b predicted that jobs in nonprofessional
occupations would have higher levels of physical demands and
lower levels of work conditions than jobs in professional occupations. As shown in Table 4, this hypothesis was supported, as
jobs in nonprofessional occupations had higher levels for physical demands, t(789) = 12.20, r2 = .16, p < .001, and lower levels of
work conditions, t(789) = 8.84, r2 = .09, p < .001. Third, hypothesis 2c predicted that jobs in health-focused occupations would
have higher levels of task significance than manufacturing jobs. As
shown in Table 4, this hypothesis was also supported, as the jobs
in the health-focused occupations had higher levels of task significance, t(41) = 2.78, r2 = .06, p < .05. Finally, hypothesis 2d predicted
Table 4
Means of Jobs across Occupational Categories.
Work characteristics
Professional
Nonprofessional
Job complexity† , **
Information processing**
Problem solving† , **
Skill variety**
Specialization**
Work scheduling autonomy**
Decision-making autonomy† , **
Work methods autonomy**
Physical demands**
Work conditions**
3.63
4.20
3.76
4.03
3.71
4.15
3.82
3.93
1.91
3.67
Health-focused
3.23
3.69
3.44
3.68
3.48
3.51
3.26
3.43
2.79
3.14
Manufacturing
Task significance† , *
4.52
Commercial
4.24
Manufacturing
Differences between Occupations
As in the original WDQ validation, our second set of hypotheses
suggested that jobs within broad occupational categories would
differ in certain work characteristics. First, hypothesis 2a predicted that knowledge and autonomy characteristics would be
higher for jobs in professional than in nonprofessional occupations. As shown in Table 4, jobs in professional occupations had
higher levels for all knowledge characteristics: job complexity,
t(677) = 6.56, r2 = .05, p < .001; information processing, t(789) = 9.79,
r2 = .11, p < .001; problem solving, t(654) = 5.98, r2 = .05, p < .001;
skill variety, t(789) = 6.61, r2 = .05, p < .001; and specialization
t(789) = 3.93, r2 = .02, p < .001. Also, all autonomy characteristics were higher in professional occupations: work scheduling
1
Full standardized factor loadings are available from the first author.
Occupational category
Interaction outside organization† , **
Note. All samples included.
†
Equal variances not assumed.
*
p < .05,
**
p < .001.
3.86
2.77
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J.A. Bayona et al. / Journal of Work and Organizational Psychology 31 (2015) 187–200
that jobs in commercial occupations would have higher levels of
interaction outside organization than manufacturing occupations.
This hypothesis was also supported as interaction outside organization was higher for jobs in commercial occupations than in
manufacturing occupations, t(29) = 4.97, r2 = .21, p < .001.
Relationshi Work Characteristics and Outcomes
Hypothesis 3a predicted that task, knowledge, and social characteristics would be positively related to job satisfaction. As shown
in Table 5, all seven task characteristics were significantly related to
job satisfaction, ranging in magnitude from .18 to .34 (mean correlation of .29). On the other hand, 4 out of 5 knowledge characteristics
were significantly related to job satisfaction, ranging in magnitude
from .15 to .23 (mean correlation of .19). Finally, for the social characteristics, only social support (.30) and feedback from others (.12)
were related to job satisfaction, thus hypothesis 3a was supported
for 13 out of 17 work characteristics.
Hypothesis 3b predicted that task, knowledge, and social characteristics would be positively related to perceived performance. As
shown in Table 5, all seven task characteristics were significantly
related to perceived performance, ranging in magnitude from .26
to .35 (mean correlation of .31). Also all five knowledge characteristics were significantly related to perceived performance, ranging in
magnitude from .08 to .40 (mean correlation of .28). Finally, four out
of five social characteristics were significantly related to perceived
performance, ranging in magnitude from .13 to .31 (mean correlation of .19). Thus, hypothesis 3b was supported for 16 out of 17
work characteristics.
The last set of hypotheses predicted that knowledge, social, and
context characteristics would incrementally predict job satisfaction
(4a) and perceived performance (4b) beyond task characteristics.
To test these hypotheses, we conducted a hierarchical regression
in which we first regressed job satisfaction or perceived performance on three control variables (age, organizational tenure, and
education) as the first step, task characteristics as the second step,
knowledge characteristics as the third step, social characteristics as
the fourth step, and work context characteristics as the fifth step.
As shown in Table 6, for the job satisfaction model, control variables
explained only small amounts of variance (5%); however, when
knowledge, social, and work context characteristics are introduced,
they explained additional amounts of variance R2 = .05, p < .01. On
the other hand, for the perceived performance model, the introduction of control variables explained small amounts of variance
(6%) and the introduction of knowledge, social, and work context
characteristics explained additional amounts of variance, R2 = .08,
p < .01.
Taking these small values into account, additional analyses
were conducted for each sample. As shown in Table 6, the social
characteristics explain medium to small amounts of variance for
job satisfaction in the university, R2 = .15, p < .01, manufacture,
R2 = .03, p < .01, and different organization sample R2 = .04,
p < .01. On the other hand, knowledge characteristics explained
significant amounts of variance for perceived performance in
the university, R2 = .17, p < .01, and manufacture organization
R2 = .07, p < .01 samples. Therefore, our results (general and segregated) provide some support for hypothesis 4a and 4b, especially
for knowledge and social characteristics; however, work context
characteristics explained only a small amount of variance for both
job satisfaction and perceived performance.
Common Method Bias
As with all self-reported data, there is a potential for the occurrence of common method bias; in order to control this, we used the
common latent factor method (CLF), in which “items are allowed
to load on their theoretical constructs, as well as on a latent
common methods variance factor, and the significance of the
structural parameters is examined both with and without the
latent common methods variance factor in the model” (Podsakoff,
MacKenzie, Lee, & Podsakoff, 2003, p. 891). Taking this into account,
we compared the original 21-factor model for the full sample
(Table 3) and a 21-factor model in which the 77 items were allowed
to load on their original factors, as well as on a CLF. The results for
the 21-factor CLF model (␹2 = 6125, df = 2635, p < .001, ␹2 /df = 2.33,
CFI = .90, SRMR = .06, RMSEA = .04) produced a small change in the
model fit (␹2 change = 219, df change = 4, p < .001, ␹2 /df change = .07,
no changes in CFI, SRMR, or RMSEA), what represented an slightly
improved fit compared with the original 21-factor model presented
in Table 3; however, when analyzing the significance of the structural parameters in both models (with and without the CLF), no
significant changes in parameter estimates were found between
the two models, these results indicating that the amount of variance
due to common method bias is relatively small.
Discussion
The purpose of this study was to test the validity of a Spanish
version of the WDQ developed by Morgeson and Humphrey (2006).
The questionnaire was administrated to 831 job incumbents working in 17 ISIC economic sectors. The CFA results indicated support
for a 21-factor solution; this is in line with previous validations in
German (Stegmann et al., 2010) and Italian (Zaniboni et al., 2013).
Furthermore, the internal consistency reliabilities for almost all
scales are above .70. As in the original validation (Morgeson &
Humphrey, 2006), the Spanish version of the WDQ was able to
detect expected differences in work characteristics across different
sets of occupations, providing construct validity evidence. In addition, we found that knowledge, social, and context characteristics
incrementally predict job satisfaction and perceived performance
beyond task characteristics.
As our results supported the validity of the Spanish version of the
WDQ, the study further contributes to the generalization of work
characteristics taxonomy proposed by Morgeson and Humphrey
(2006). Thus, our results from three Colombian samples provide
further evidence for the generalizability of the scale in different
cultural settings. The WDQ validation in a cultural setting different
from the one in which they were developed and validated (USA,
Western Europe) gives additional support to the structure of work
characteristics that are relevant for all works and organizations.
The confirmation of the 21-factor structure was expected, as
Colombia during the last 20 years has opened its borders to new
organizations and work arrangements and has begun to switch
from an agriculture and production economy to a more intense
service economy (Ogliastri, 2007). This is consistent with the
importance given to social and knowledge characteristics which are
distinctive of service organizations beyond the traditional task and
work context characteristics that are typical of production industries.
The Spanish version of the WDQ obtained better psychometric results than similar work characteristics instruments that were
tested in the Spanish speaking countries context such as the JDS
(Fuertes et al., 1996) and presented a clear internal structure of the
model, showing high reliability among almost all 21 work characteristics. The work context characteristic that showed some low
reliability (ergonomics) included a reverse coded item, a relatively
common phenomena that is also presented in other organizational
behavior questionnaire validations (Podsakoff et al., 2003). However, when the problem item is eliminated, the factor reliability
improves considerably (␣ = .84). In addition, this work characteristic was the one with the lowest reliability in the original validation
of Morgeson and Humphrey (2006).
Table 5
Intercorrelations among Study Variables.
1
2
3
4
5
6
7
8
9
10
11
–
.69**
.69**
.27**
.24**
.37**
.29**
–
.72**
.31**
.27**
.33**
.33**
–
.27**
.25**
.36**
.37**
–
.35**
.22**
.27**
–
.33**
.37**
.06
.28**
.22**
.23**
.18**
.08*
.29**
.31**
.30**
.29**
.06
.32**
.29**
.29**
.27**
.23**
.43**
.31**
.42**
.21**
.24**
.10**
.08*
.14**
.10**
.26**
.13**
.10**
.17**
.13**
.25**
.15**
.12**
.13**
.09*
**
**
**
12
–
.57**
–
.09*
.33**
.30**
.38**
.36**
−.09*
.23**
.09*
.21**
.25**
−.05
.26**
.19**
.24**
.26**
–
.35**
.17**
.26**
.13**
–
.52**
.55**
.42**
–
.56**
.41**
–
.55**
.22**
.24**
.21**
.16**
.11**
.35**
.25**
.20**
.21**
.14**
.36**
.10**
.05
.20**
.22**
.38**
.10**
.07
.18**
.29**
−.06
.10**
.13**
.03
−.07*
.18**
.27**
.29**
.20**
.14**
.16**
.24**
.19**
.17**
.09*
.21**
.26**
.23**
.14**
.06
**
**
**
**
**
13
14
15
16
–
.56**
.09**
.07*
–
.17**
.04
18
19
20
.19**
−.00
.19**
.11**
–
−.45**
.46**
−.06
–
−.40**
.41**
–
−.11**
.12**
.13**
.25**
.17**
−.11**
.02
.17**
.09**
21
22
–
.21**
.24**
.18**
.08*
.13**
–
.13**
.07*
.30**
.43**
.27
−.24**
.29**
−.05
.24
−.16**
.20**
.04
.25
−.17**
.25**
.02
.11
−.03
.08*
.10**
.12
.01
.06
.18**
.27
−.12**
.25**
.06
.20
−.07*
.19**
.11**
−.01
−.15**
−.05
−.06
.13
−.15**
.15**
.10**
.02
−.02
.04
.11**
.07
−.01
.05
.19**
.08
.10**
.02
.37**
.30
−.07*
.24**
.06
.06
.08*
.01
.20**
.07
−.03
.04
.16**
.34**
.28**
.33**
.32**
.31**
.33**
.18**
.26**
.27**
.35**
.31**
.30**
.31**
.35**
.05
.08**
.15**
.29**
.15**
.26**
.23**
.37**
.23**
.40**
.30**
.31**
.03
.20**
.04
.15**
*
17
*
**
*
–
.27**
**
.09
−.08*
.17**
.03
.06
.04
–
–
.07
.17**
–
.37**
J.A. Bayona et al. / Journal of Work and Organizational Psychology 31 (2015) 187–200
Task characteristics
1. Work scheduling autonomy
2. Decision-making autonomy
3. Work methods autonomy
4. Task variety
5. Task significance
6. Task identity
7. Feedback from job
Knowledge characteristics
8. Job complexity
9. Information processing
10. Problem solving
11. Skill variety
12. Specialization
Social characteristics
13. Social support
14. Initiated interdependence
15. Received interdependence
16. Interaction outside organization
17. Feedback from others
Work context characteristics
18. Ergonomics
19. Physical demands
20. Work conditions
21. Equipment use
Outcomes
22. Job satisfaction
23. Perceived performance
Note. All samples included. n ranges from 810 to 831.
*
p < .05,
**
p < .01.
195
196
J.A. Bayona et al. / Journal of Work and Organizational Psychology 31 (2015) 187–200
Table 6
Incremental Validity of Work Characteristics on Job Satisfaction and Perceived Performance.
Work outcomes
Job satisfaction
Predictor
Step 1 R2
Age, Tenure, Education
Step 2 R2
Task Characteristics
Step 3 R2
Knowledge Characteristics
Step 4 R2
Social Characteristics
Step 5 R2
Work Context Characteristics
Total R2
**
*
Sample 1
Sample 2
Sample 3
Perceived performance
All samples
Sample 1
Sample 2
Sample 3
All samples
.06**
.06
.05**
.05**
.07**
.05
.09**
.06**
.19**
.18*
.18**
.16**
.17**
.31**
.25**
.20**
.02**
.05*
.02**
.01**
.07**
.17**
.01**
.05**
.03**
.15**
.04**
.02**
.04**
.05**
.03**
.02**
.03**
.01*
.02**
.02**
.01**
.03**
.00**
.01**
.33**
.45*
.31**
.26**
.36**
.61**
.38**
.34**
p < .01,
p < .05.
Although all hypotheses were supported in some degree, two
unexpected relations emerged in the present Spanish validation.
The first unexpected result was the differential role of knowledge and social characteristics in job satisfaction and perceived
performance (Table 6). The R2 in job satisfaction (14%) due to
social characteristics, and in perceived performance (19%) due to
knowledge characteristics in the university sample may be related
with the observations of Michael Campion in the interdisciplinary
approach to work design (Campion, 1988), that states that different
job design approaches influence different outcomes (e.g., the motivational approach is more correlated with satisfaction outcomes
than the rest of the approaches); in this case, what was found was
that in this sample, some work characteristics influence different
outcomes. These results could indicate that when a work redesign
is imminent (especially in knowledge-oriented organizations as the
university), it is important to pay attention to which specific outcomes are of interest to change and depending on this, it will be
necessary to evaluate only some work characteristics.
The second unexpected result was related to some differences
in the convergent and discriminant validity results on autonomy
and social characteristics (Table 2). From the psychometric perspective, these results on low divergent validity among autonomy
(work scheduling, decision-making and, work methods) and interdependence (initiated and received) may be explained by the fact
that they are composites of a more general factor (autonomy and
interdependence) and for this reason it is expected that MSV values
will be greater than those in the other variables.
Finally, we have to be cautious with the problem solving variable, due to its non-significant interrater reliability, low AVE,
and high MSV. These results indicate that this particular variable
share a high portion of variance with other variables, in particular
with information processing. Because of this, the analysis of these
variables should be treated with caution in future Spanish WDQ
administrations.
related to institutional collectivism (degree in which organizational
practices encourage and reward collective distribution of resources
and collective action); this relation is important in order to redesign
(increase) autonomy in positions where high institutional collectivism is present.
With regard to research, the WDQ is a tool that allows to investigate the impact of different work configurations on organizational
and personal outcomes and let open a research line of the influence
of different mediators and moderators in the relation between work
characteristics and personal and organizational outcomes (e.g., cultural characteristics).
Implications for Practice and Research
Conclusion
For practitioners, a broader range of work design potentials is
possible beyond the traditional five job characteristics of the JDS;
however, it is important that practitioners be fully aware of potential cultural influences in the work design practice. In the case of
Latin-America countries, a deep collectivism value can be found,
and in Colombia there is an important role of collectivism and rejection to individualism (Ogliastri, 2007). In an article from the GLOBE
project (Dorfman, Javidan, Hanges, Dastmalchian, & House, 2012),
the authors report that the autonomous dimension (tendencies to
act independently without relying on others) is strongly negative
The Spanish version of the WDQ is a validated and reliable
instrument to assess work characteristics in the Spanish speaking
context. Our study provided evidence for the validity of a Spanish
version of the scale and presented further support for the generalization of the 21-factor of work design characteritics in different
cultural settings that included particular relations between knowledge and social characteristics and job satisfaction and perceived
performance. We hope that the introduction of this instrument will
stimulate further research and practice on work design in Spanish
speaking countries.
Limitations
Two major drawback limited the present research: first, the
presence of some level of common method bias, which implies
that the results must be interpreted with caution, even though the
CLF test results indicated that variance due to common method
is between the acceptable limits. This is consistent with previous
research on common method variance, which has concluded that
while common method bias may be present, it may not always significantly affect the results and conclusions drawn from the data
(Crampton & Wagner, 1994; Doty & Glick, 1998). The second limitation was the sample method selection; although we used three
different samples and almost all occupational groups of the ISIC
were considered, some groups were sub-represented (e.g., arts,
entertainment, and recreation); besides, it is also important to consider that half of the labor market in Colombia is informal and the
conclusions of this study can apply only to the workers that are
inside the formal labor market (50% of the Colombian total labor
force). Future research should consider the structure of work characteristics in jobs included in the informal labour market. They
represent in developing countries an important amount of the total
economy and deserve a better analysis and understanding.
J.A. Bayona et al. / Journal of Work and Organizational Psychology 31 (2015) 187–200
Conflict of Interest
197
Appendix.
The authors of this article declare no conflict of interest.
Financial Support
This research has been founded by Pontificia Universidad Javeriana and sponsored by the project PSI2012-36557 funded by DGICYT
and the funding of the Generalitat Valenciana for research groups
of excellence PROMETEO 2012/048.
Las siguientes preguntas hacen referencia a varias características que se pueden presentar en su actual trabajo. Usando la escala
que se presenta a continuación, indique en qué medida está de
acuerdo con cada afirmación (1 = muy en desacuerdo, 2 = algo en
desacuerdo, 3 = ni de acuerdo, ni en desacuerdo, 4 = algo de acuerdo,
5 = muy de acuerdo).
Original English Version
Adapted Spanish Version
Task Characteristics
Características de la Tarea
Work Scheduling Autonomy
Autonomía en la organización del trabajo
The job allows me to make my own decisions about how to schedule my work.
El trabajo me permite tomar mis propias decisiones sobre cómo organizarlo.
The job allows me to decide on the order in which things are done on the job.
El trabajo me permite decidir el orden en que se hacen las cosas.
The job allows me to plan how I do my work.
Decision-Making Autonomy
The job gives me a chance to use my personal initiative or judgment in carrying
out the work.
El trabajo me permite planificar cómo hacer mis tareas.
Autonomía en la toma de decisiones
El trabajo me da la oportunidad de usar mi iniciativa o criterio para
realizarlo.
The job allows me to make a lot of decisions on my own.
El trabajo me permite tomar muchas decisiones por mi cuenta.
The job provides me with significant autonomy in making decisions.
El trabajo me proporciona mucha autonomía en la toma de decisiones.
Work Methods Autonomy
Autonomía en los Métodos Utilizados en el Trabajo
The job allows me to make decisions about what methods I use to complete my
work.
El trabajo me permite tomar decisiones sobre los métodos que uso para
realizarlo.
The job gives me considerable opportunity for independence and freedom in
how I do the work.
El trabajo me ofrece muchas posibilidades de independencia y libertad para
decidir cómo hacerlo.
The job gives me considerable opportunity for independence and freedom in
how I do the work.
Task Variety
El trabajo me permite decidir por mi cuenta cómo organizarme para hacerlo.
Variedad de la Tarea
The job involves a great deal of task variety.
El trabajo incluye una gran variedad de tareas.
The job involves doing a number of different things.
El trabajo implica hacer muchas cosas diferentes.
The job requires the performance of a wide range of tasks.
El trabajo requiere la realización de una amplia gama de tareas.
The job involves performing a variety of tasks.
Task Significance
The results of my work are likely to significantly affect the lives of other people.
The job itself is very significant and important in the broader scheme of things.
El trabajo implica la realización de una considerable variedad de tareas.
Significado de la Tarea
Es bastante probable que, el resultado de mi trabajo tenga efectos
significativos en las vidas de otras personas.
El trabajo para mí es significativo e importante.
The job has a large impact on people outside the organization.
El trabajo tiene un impacto importante en personas externas a la
organización.
The work performed on the job has a significant impact on people outside the
organization.
El resultado de este trabajo tiene un impacto significativo en personas
externas a la organización.
Task Identity
Identidad de la Tarea
The job involves completing a piece of work that has an obvious beginning and
end.
El trabajo implica completar partes del mismo que tienen un comienzo y
final claros.
The job is arranged so that I can do an entire piece of work from beginning to
end.
El trabajo está organizado de manera que puedo realizar una unidad
completa del mismo, desde el comienzo hasta el final.
The job provides me the chance to completely finish the pieces of work I begin.
The job allows me to complete work I start.
Feedback From Job
El trabajo me proporciona la oportunidad de terminar lo que empiezo.
El trabajo me permite completar las actividades que inicio.
Retroalimentación desde el Trabajo
The work activities themselves provide direct and clear information about the
effectiveness (e.g. quality and quantity) of my job performance.
Las actividades de mi trabajo me proporcionan por sí mismas información
directa y clara sobre la eficacia de mi desempeño en el mismo (por ejemplo,
calidad y cantidad).
The job itself provides feedback on my performance.
El trabajo en sí mismo me proporciona retroalimentación sobre mi
desempeño.
The job itself provides me with information about my performance.
El trabajo en sí mismo me proporciona información sobre mi desempeño.
198
J.A. Bayona et al. / Journal of Work and Organizational Psychology 31 (2015) 187–200
Original English Version
Adapted Spanish Version
Knowledge Characteristics
Características del Conocimiento
Job Complexity
Complejidad del Trabajo
The job requires that I only do one task or activity at a time. (reverse scored)
The tasks on the job are simple and uncomplicated. (reverse scored)
The job comprises relatively uncomplicated tasks. (reverse scored)
The job involves performing relatively simple tasks. (reverse scored)
Information Processing
El trabajo requiere hacer sólo una tarea o actividad a la vez. (codificación
inversa)
Las tareas del trabajo son simples y sin complicaciones. (codificación inversa)
El trabajo abarca tareas relativamente sencillas. (codificación inversa)
El trabajo incluye el desempeño de tareas relativamente simples.
(codificación inversa)
Procesamiento de Información
The job requires me to monitor a great deal of information.
El trabajo requiere manejar una gran cantidad de información.
The job requires that I engage in a large amount of thinking.
El trabajo requiere pensar mucho.
The job requires me to keep track of more than one thing at a time.
El trabajo requiere realizar más de una cosa a la vez.
The job requires me to analyze a lot of information.
El trabajo me exige analizar una gran cantidad de información.
Problem Solving
The job involves solving problems that have no obvious correct answer.
The job requires me to be creative.
The job often involves dealing with problems that I have not met before.
The job requires unique ideas or solutions to problems.
Skill Variety
Solución de Problemas
El trabajo incluye la solución de problemas que no tienen una respuesta
correcta clara.
El trabajo requiere que sea creativo.
El trabajo implica a menudo gestionar problemas que no me he encontrado
antes.
El trabajo requiere ideas y soluciones únicas para los problemas.
Variedad de Habilidades
The job requires a variety of skills.
El trabajo requiere una variedad de destrezas.
The job requires me to utilize a variety of different skills in order to complete the
work.
The job requires me to use a number of complex or high-level skills.
El trabajo requiere la utilización distintas destrezas para realizarlo.
The job requires the use of a number of skills.
Specialization
The job is highly specialized in terms of purpose, tasks, or activities.
The tools, procedures, materials, and so forth used on this job are highly
specialized in terms of purpose.
El trabajo requiere la utilización de una variedad de destrezas complejas o
de alto nivel.
El trabajo requiere el uso de diversas destrezas.
Especialización
El trabajo es altamente especializado en su propósito, tareas o actividades.
Las herramientas, procedimientos, materiales etc. utilizados en este trabajo
son altamente especializados debido a su propósito.
The job requires very specialized knowledge and skills.
El trabajo requiere conocimientos y destrezas muy especializados.
The job requires a depth of knowledge and expertise.
El trabajo requiere un conocimiento profundo y ser experto.
Social Characteristics
Características Sociales
Social Support
Apoyo Social
I have the opportunity to develop close friendships in my job.
En mi trabajo tengo la oportunidad de desarrollar buenas amistades.
I have the chance in my job to get to know other people.
En mi trabajo tengo la oportunidad de conocer a otras personas.
I have the opportunity to meet with others in my work.
En mi trabajo tengo la oportunidad de encontrarme con otros.
My supervisor is concerned about the welfare of the people that work for
him/her.
People I work with take a personal interest in me.
People I work with are friendly.
Initiated Interdependence
The job requires me to accomplish my job before others complete their job.
Mi supervisor se interesa por el bienestar de las personas que trabajan para
él o ella.
Las personas con las que trabajo se interesan por mí personalmente.
Las personas con las que trabajo son amistosas.
Interdependencia Iniciada
El trabajo requiere que realice mis tareas antes de que otros completen las
suyas.
Other jobs depend directly on my job.
Otros trabajos dependen directamente del mío.
Unless my job gets done, other jobs cannot be completed.
Si mi trabajo no está terminado no se puede completar el de otros.
Received Interdependence
The job activities are greatly affected by the work of many different people for
its completion.
My job depends on the work of many different people for its completion.
My job cannot be done unless others do their work.
Interdependencia Recibida
Las actividades de mi trabajo se ven muy afectadas por el de otras personas.
La realización de este trabajo requiere la aportación del trabajo de otras
personas diferentes.
No puedo hacer mi trabajo a menos que otros hagan el suyo.
J.A. Bayona et al. / Journal of Work and Organizational Psychology 31 (2015) 187–200
Original English Version
Interaction Outside Organization
199
Adapted Spanish Version
Interacción fuera de la Organización
The job requires spending a great deal of time with people outside my
organization.
El trabajo requiere emplear mucho tiempo con personas externas a mi
organización.
The job involves interaction with people who are not members of my
organization.
El trabajo implica interacción con personas que no son miembros de mi
organización.
On the job, I frequently communicate with people who do not work for the same
organization as I do.
En el trabajo con frecuencia me comunico con personas que no trabajan para
la misma organización que yo.
The job involves a great deal of interaction with people outside my organization.
El trabajo implica mucha interacción con personas externas a mi
organización.
Feedback From Others
Retroalimentación por parte de Otros
I receive a great deal of information from my manager and co-workers about my
job performance.
Recibo mucha información de mi supervisor inmediato y de mis compañeros
sobre mi desempeño en el trabajo.
Other people in the organization, such as managers and co-workers, provide
information about the effectiveness (e.g. quality and quantity) of my job
performance.
Otras personas de la organización, como supervisores y compañeros, me
proporcionan información sobre la eficacia de mi desempeño en el trabajo (por
ejemplo, calidad y cantidad).
I receive feedback on my performance from other people in my organization
(such as my manager or co-workers).
Recibo información de otras personas en mi organización (como mi
supervisor inmediato o compañeros) sobre mi desempeño.
Work Context
Contexto del Trabajo
Ergonomics
Ergonomía
The seating arrangements on the job are adequate (e.g. ample opportunities to
sit, comfortable chairs, good postural support).
La disposición de los asientos en el trabajo es adecuada (por ejemplo,
amplias oportunidades para sentarse, sillas cómodas, buen apoyo postural).
The work place allows for all size differences between people in terms of
clearance, reach, eye height, leg room, etc.
El lugar del trabajo se ajusta a las diferencias personales en término de
espacio, alcance, altura de la vista, espacio para las piernas, etc.
The job involves excessive reaching. (reverse scored)
El trabajo implica excesivos esfuerzos para alcanzar las cosas. (codificación
inversa)
Physical Demands
Demandas Físicas
The job requires a great deal of muscular endurance.
El trabajo requiere una gran resistencia muscular.
The job requires a great deal of muscular strength.
El trabajo requiere una gran fuerza muscular.
The job requires a lot of physical effort.
Work Conditions
The work place is free from excessive noise.
The climate at the work place is comfortable in terms of temperature and
humidity.
The job has a low risk of accident.
The job takes place in an environment free from health hazards (e.g., chemicals,
fumes, etc.).
The job occurs in a clean environment.
Equipment Use
El trabajo requiere mucho esfuerzo físico.
Condiciones del Trabajo
El lugar de trabajo está libre de ruidos excesivos.
El clima en el lugar de trabajo es confortable (por ejemplo: temperatura y
humedad).
El trabajo tiene un riesgo de accidente bajo.
El trabajo se hace en un entono libre de peligros para la salud (por ejemplo
sustancias químicas, gases, etc.).
El trabajo se hace en un ambiente limpio.
Uso de Equipo
The job involves the use of a variety of different equipment.
El trabajo implica el uso de distintos equipamientos.
The job involves the use of complex equipment or technology.
El trabajo incluye el uso de equipos o tecnologías complejas.
A lot of time was required to learn the equipment used on the job.
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